Drift correction in localization microscopy using entropy minimization

VPS13B is localized at the interface between Golgi cisternae and is a functional partner of FAM177A1

Mutations in VPS13B, a member of a protein family implicated in bulk lipid transport between adjacent membranes, cause Cohen syndrome. VPS13B is known to be concentrated in the Golgi complex, but its precise location within this organelle and thus the site(s) where it achieves lipid transport remains unclear. Here, we show that VPS13B is localized at the interface between proximal and distal Golgi subcompartments and that Golgi complex reformation after Brefeldin A (BFA)-induced disruption is delayed in VPS13B KO cells. This delay is phenocopied by the loss of FAM177A1, a Golgi complex protein of unknown function reported to be a VPS13B interactor and whose mutations also result in a developmental disorder. In zebrafish, the vps13b ortholog, not previously annotated in this organism, genetically interacts with fam177a1. Collectively, these findings raise the possibility that bulk lipid transport by VPS13B may play a role in the dynamics of Golgi membranes and that VPS13B may be assisted in this function by FAM177A1.

Modeling Scanning Electrochemical Cell Microscopy (SECCM) in Twisted Bilayer Graphene

Twisted 2D-flat band materials host exotic quantum phenomena and novel moiré patterns, showing immense promise for advanced spintronic and quantum applications. Here, we evaluate the nanostructure-activity relationship in twisted bilayer graphene by modeling it under the scanning electrochemical cell microscopy setup to resolve its spatial moiré domains. We solve the steady state ion transport inside a 3D nanopipette to isolate the current response at AA and AB domains. Interfacial reaction rates are obtained from a modified Marcus-Hush-Chidsey theory combining input from a tight binding model that describes the electronic structure of bilayer graphene. High rates of redox exchange are observed at the AA domains, an effect that reduces with diminished flat bands or a larger cross-sectional area of the nanopipette. Using voltammograms, we identify an optimal voltage that maximizes the current difference between the domains. Our study lays down the framework to electrochemically capture prominent features of the band structure that arise from spatial domains and deformations in 2D flat-band materials.

Toward drift-free high-throughput nanoscopy through adaptive intersection maximization

Single-molecule localization microscopy (SMLM) often suffers from suboptimal resolution due to imperfect drift correction. Existing marker-free drift correction algorithms often struggle to reliably track high-frequency drift and lack the computational efficiency to manage large, high-throughput localization datasets. We present an adaptive intersection maximization-based method (AIM) that leverages the entire dataset's information content to minimize drift correction errors, particularly addressing high-frequency drift, thereby enhancing the resolution of existing SMLM systems. We demonstrate that AIM can robustly and efficiently achieve an angstrom-level tracking precision for high-throughput SMLM datasets under various imaging conditions, resulting in an optimal resolution in simulated and biological experimental datasets. We offer AIM as one simple, model-free software for instant resolution enhancement with standard CPU devices.

Multiplexed DNA-PAINT Imaging of the Heterogeneity of Late Endosome/Lysosome Protein Composition

Late endosomes/lysosomes (LELs) are crucial for numerous physiological processes and their dysfunction is linked to many diseases. Proteomic analyses have identified hundreds of LEL proteins, however, whether these proteins are uniformly present on each LEL, or if there are cell-type dependent LEL sub-populations with unique protein compositions is unclear. We employed a quantitative, multiplexed DNA-PAINT super-resolution approach to examine the distribution of six key LEL proteins (LAMP1, LAMP2, CD63, TMEM192, NPC1 and LAMTOR4) on individual LELs. While LAMP1 and LAMP2 were abundant across LELs, marking a common population, most analyzed proteins were associated with specific LEL subpopulations. Our multiplexed imaging approach identified up to eight different LEL subpopulations based on their unique membrane protein composition. Additionally, our analysis of the spatial relationships between these subpopulations and mitochondria revealed a cell-type specific tendency for NPC1-positive LELs to be closely positioned to mitochondria. Our approach will be broadly applicable to determining organelle heterogeneity with single organelle resolution in many biological contexts.

Summary

This study develops a multiplexed and quantitative DNA-PAINT super-resolution imaging pipeline to investigate the distribution of late endosomal/lysosomal (LEL) proteins across individual LELs, revealing cell-type specific LEL sub-populations with unique protein compositions, offering insights into organelle heterogeneity at single-organelle resolution.

Quantitative Single-Molecule Localization Microscopy

Super-resolution fluorescence microscopy allows the investigation of cellular structures at nanoscale resolution using light. Current developments in super-resolution microscopy have focused on reliable quantification of the underlying biological data. In this review, we first describe the basic principles of super-resolution microscopy techniques such as stimulated emission depletion (STED) microscopy and single-molecule localization microscopy (SMLM), and then give a broad overview of methodological developments to quantify super-resolution data, particularly those geared toward SMLM data. We cover commonly used techniques such as spatial point pattern analysis, colocalization, and protein copy number quantification but also describe more advanced techniques such as structural modeling, single-particle tracking, and biosensing. Finally, we provide an outlook on exciting new research directions to which quantitative super-resolution microscopy might be applied.

Constructing a cost-efficient, high-throughput and high-quality single-molecule localization microscope for super-resolution imaging

Single-molecule localization microscopy (SMLM) leverages the power of modern optics to unleash ultra-precise structural nanoscopy of complex biological machines in their native environments as well as ultra-sensitive and high-throughput medical diagnostics with the sensitivity of a single molecule. To achieve this remarkable speed and resolution, SMLM setups are either built by research laboratories with strong expertise in optical engineering or commercially sold at a hefty price tag. The inaccessibility of SMLM to life scientists for technical or financial reasons is detrimental to the progress of biological and biomedical discoveries reliant on super-resolution imaging. In this work, we present the NanoPro, an economic, high-throughput, high-quality and easy-to-assemble SMLM for super-resolution imaging. We show that our instrument performs similarly to the most expensive, best-in-class commercial microscopes and rivals existing open-source microscopes at a lower price and construction complexity. To facilitate its wide adoption, we compiled a step-by-step protocol, accompanied by extensive illustrations, to aid inexperienced researchers in constructing the NanoPro as well as assessing its performance by imaging ground-truth samples as small as 20 nm. The detailed visual instructions make it possible for students with little expertise in microscopy engineering to construct, validate and use the NanoPro in <1 week, provided that all components are available.

Estimating the localization spread function of static single-molecule localization microscopy images

Single-molecule localization microscopy (SMLM) permits the visualization of cellular structures an order of magnitude smaller than the diffraction limit of visible light, and an accurate, objective evaluation of the resolution of an SMLM data set is an essential aspect of the image processing and analysis pipeline. Here, we present a simple method to estimate the localization spread function (LSF) of a static SMLM data set directly from acquired localizations, exploiting the correlated dynamics of individual emitters and properties of the pair autocorrelation function evaluated in both time and space. The method is demonstrated on simulated localizations, DNA origami rulers, and cellular structures labeled by dye-conjugated antibodies, DNA-PAINT, or fluorescent fusion proteins. We show that experimentally obtained images have LSFs that are broader than expected from the localization precision alone, due to additional uncertainty accrued when localizing molecules imaged over time.

Thermal drift correction method for laboratory nanocomputed tomography based on global mixed evaluation

Nanocomputed tomography (nanoCT) is an effective tool for the nondestructive observation of 3D structures of nanomaterials; however, it requires additional correction phantom to reduce artifacts induced by the focal drift of the X-ray source and mechanical thermal expansion. Drift correction without a correction phantom typically uses rapidly acquired sparse projections to align the original projections. The noise and brightness difference in the projections limit the accuracy of existing feature-based methods such as locality preserving matching (LPM) and random sample consensus (RANSAC). Herein, a rough-to-refined correction framework based on global mixed evaluation (GME) is proposed for precise drift estimation. First, a new evaluation criterion for projection alignment, named GME, which comprises the structural similarity (SSIM) index and average phase difference (APD), is designed. Subsequently, an accurate projection alignment is achieved to estimate the drift by optimizing the GME within the proposed correction framework based on the rough-to-refined outlier elimination strategy. The simulated 2D projection alignment experiments show that the accuracy of the GME is improved by 14× and 12× than that of the mainstream feature-based methods LPM and RANSAC, respectively. The proposed method is validated through actual 3D imaging experiments.

Influence of drift correction precision on super-resolution localization microscopy

Super-resolution localization microscopy (SRLM) breaks the diffraction limit successfully and improves the resolution of optical imaging systems by nearly an order of magnitude. However, SRLM typically takes several minutes or longer to collect a sufficient number of image frames that are required for reconstructing a final super-resolution image. During this long image acquisition period, system drift should be tightly controlled to ensure the imaging quality; thus, several drift correction methods have been developed. However, it is still unclear whether the performance of these methods is able to ensure sufficient image quality in SRLM. Without a clear answer to this question, it is hard to choose a suitable drift correction method for a specific SRLM experiment. In this paper, we use both theoretical analysis and simulation to investigate the relationship among drift correction precision, localization precision, and position estimation precision. We propose a concept of relative localization precision for evaluating the effect of drift correction on imaging resolution, which would help to select an appropriate drift correction method for a specific experiment.

Super-Resolution Microscopy for Structural Cell Biology

Super-resolution microscopy techniques, and specifically single-molecule localization microscopy (SMLM), are approaching nanometer resolution inside cells and thus have great potential to complement structural biology techniques such as electron microscopy for structural cell biology. In this review, we introduce the different flavors of super-resolution microscopy, with a special emphasis on SMLM and MINFLUX (minimal photon flux). We summarize recent technical developments that pushed these localization-based techniques to structural scales and review the experimental conditions that are key to obtaining data of the highest quality. Furthermore, we give an overview of different analysis methods and highlight studies that used SMLM to gain structural insights into biologically relevant molecular machines. Ultimately, we give our perspective on what is needed to push the resolution of these techniques even further and to apply them to investigating dynamic structural rearrangements in living cells. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A mean shift algorithm for drift correction in localization microscopy

Single-molecule localization microscopy techniques transcend the diffraction limit of visible light by localizing isolated emitters sampled stochastically. This time-lapse imaging necessitates long acquisition times, over which sample drift can become large relative to the localization precision. Here, we present an efficient and robust method for estimating drift, using a simple peak-finding algorithm based on mean shifts that is effective for single-molecule localization microscopy in two or three dimensions.